5 V’s of Big Data

5 V’s of Big Data

Volume

  • The main characteristic that makes data “big” is the sheer volume. It makes no sense to focus on minimum storage units because the total amount of information is growing exponentially every year.
  • In 2010, Thomson Reuters estimated in its annual report that it believed the world was “awash with over 800 exabytes of data and growing.”
  • For that same year, EMC, a hardware company that makes data storage devices, though it was closer to 900 exabytes and would grow by 50 percent every year. No one really knows how much new data is being generated, but the amount of information being collected is huge. You can master your skills on big data through big data online training

Velocity:

  • Velocity refers to the high speed of accumulation of data.
  • In Big Data velocity data flows in from sources like machines, networks, social media, mobile phones, etc.
  • There is a massive and continuous flow of data. This determines the potential of data that how fast the data is generated and processed to meet the demands. Sampling data can help in dealing with the issue like ‘velocity’.
  • Example: There are more than 3.5 billion searches per day are made on Google. Also, Facebook users are increasing by 22%(Approx.) year by year. here are the important big data programming languages in 2020

Variety:

  • Variety refers to the nature of data that is structured, semi-structured and unstructured data.
  • Variety also refers to heterogeneous sources.
  • Variety is basically the arrival of data from new sources that are both inside and outside of an enterprise. They are classified into three types

Veracity:

  • Veracity refers to inconsistencies and uncertainty in data, that is data that is available can sometimes get messy and quality and accuracy are difficult to control.
  • Big Data is also variable because of the multitude of data dimensions resulting from multiple disparate data types and sources. you can learn more on big data through big data online course

Value:

  • After having the 4 V’s into account there comes one more V which stands for Value!. The bulk of Data having no Value is of no good to the company, unless you turn it into something useful.
  • Data in itself is of no use or importance but it needs to be converted into something valuable to extract Information. Hence, you can state that Value! is the most important V of all the 5V’s.